Effect of dietary Ginkgo biloba leaf on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii

This trial investigated the effect of dietary Ginkgo biloba leaf (GBL) on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii. 180 Crayfishes were randomly divided into three groups. One group was fed with basic diet, whereas the other two groups were fed with diets containing 1% and 3% GBL. After 32 days of feeding, GBL addition tended to increase the body weight gain rate compared with control. In 3% GBL group, the bodyweight gain rate of male crayfish was higher than that of female crayfish. While female crayfish were advantageous in terms of meat yield. Liver-related indexes were influenced by GBL addition and 3% GBL could reduce glutamic pyruvic transaminase and glutamic oxaloacetic transaminase as well as total cholesterol in male crayfish, showing its function in liver protection. Moreover, GBL addition effects on liver protection was better in male crayfish than female crayfish

Budd-Chiari Syndrome in China: A Systematic Analysis of Epidemiological Features Based on the Chinese Literature Survey

Background. Thousands of Budd-Chiari syndrome (BCS) studies have been published in China, and yet no one has explored its incidence or prevalence in the whole country. Methods. Three most commonly used Chinese language electronic databases were searched, and epidemiological data were extracted from the selected articles. Results. By the end of 2013, 20191 BCS cases were reported in China. The mean age of BCS patients was 36.29 ± 1.28 years, and ratio of male to female was 150/100. About 80% BCS patients were distributed in Henan, Shandong, Beijing, Jiangsu, and Anhui, and all of them except for Beijing were located in the downstream areas of Yellow River and the whole Huai River basin. The incidence and prevalence of BCS in China with and without the top 5 high-prevalence areas were estimated to be 0.88/million per year and 7.69/million and 0.28/million per year and 2.21/million, respectively. Conclusions. Most BCS patients in China are distributed in the downstream areas of Yellow River and the whole Huai River basin. The incidence and prevalence are comparable to those of Western countries without taking into account the top 5 high-prevalence areas

The role of serum vitamin D in patients with normal ovarian reserve undergoing the first IVF/ICSI cycle

BackgroundThe debate over the impact of vitamin D in assisted reproduction continues. The purpose of our study was to assess embryo quality and pregnancy outcomes among groups with different levels of vitamin D after the first in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) cycle in patients with normal ovarian reserve (NOR).MethodsPatients in this retrospective cohort study were divided into three groups: severe vitamin D deficiency group (25OH-D < 10 ng/ml), vitamin D deficiency group (10 ng/ml ≤ 25OH-D < 20 ng/ml), and non-vitamin D deficiency group (25OH-D ≥ 20 ng/ml). The primary outcome was clinical pregnancy, while the secondary outcomes were mature oocytes, oocyte fertilization, available cleavage embryos, available blastocysts, biochemical pregnancy, early abortion, and embryo implantation. A modified Poisson regression model and multiple linear regression analysis were conducted for the multivariate analysis.Results264 NOR patients undergoing the first IVF/ICSI cycles were included. For the primary outcome, there was no significant difference in clinical pregnancy between the severe vitamin D deficiency group and the other two groups (vitamin D deficiency group: adjusted RR = 1.026; 0.780 - 1.350; P = 0.854; non-vitamin D deficiency group: adjusted RR = 1.092; 0.743 - 1.605; P = 0.652). For all secondary outcomes, no significant differences were observed among the severe vitamin D deficiency, vitamin D deficiency, and non-vitamin D deficiency groups (P > 0.05). Exploratory subgroup analyses concerning the season of embryo transfer, phase of embryo transferred, and endometrial thickness, as well as the sensitivity analysis using logistic regression models for the primary outcome, revealed comparable clinical pregnancy rates among the groups (P > 0.05). Subgroup analysis concerning ovarian stimulation protocol indicated that in the subgroup of gonadotrophin-releasing hormone (GnRH) antagonist protocol, the clinical pregnancy rate of the non-vitamin D deficiency group was significantly higher than that of the other two groups (P < 0.05).ConclusionSerum vitamin D level was not associated with embryo quality and pregnancy outcomes for patients with NOR. Further studies with greater sample sizes and a longer follow-up period are needed to elucidate the relationships between vitamin D levels and IVF outcomes

Identification of common molecular signatures of SARS-CoV-2 infection and its influence on acute kidney injury and chronic kidney disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of COVID-19, causing hundreds of millions of confirmed cases and more than 18.2 million deaths worldwide. Acute kidney injury (AKI) is a common complication of COVID-19 that leads to an increase in mortality, especially in intensive care unit (ICU) settings, and chronic kidney disease (CKD) is a high risk factor for COVID-19 and its related mortality. However, the underlying molecular mechanisms among AKI, CKD, and COVID-19 are unclear. Therefore, transcriptome analysis was performed to examine common pathways and molecular biomarkers for AKI, CKD, and COVID-19 in an attempt to understand the association of SARS-CoV-2 infection with AKI and CKD. Three RNA-seq datasets (GSE147507, GSE1563, and GSE66494) from the GEO database were used to detect differentially expressed genes (DEGs) for COVID-19 with AKI and CKD to search for shared pathways and candidate targets. A total of 17 common DEGs were confirmed, and their biological functions and signaling pathways were characterized by enrichment analysis. MAPK signaling, the structural pathway of interleukin 1 (IL-1), and the Toll-like receptor pathway appear to be involved in the occurrence of these diseases. Hub genes identified from the protein–protein interaction (PPI) network, including DUSP6, BHLHE40, RASGRP1, and TAB2, are potential therapeutic targets in COVID-19 with AKI and CKD. Common genes and pathways may play pathogenic roles in these three diseases mainly through the activation of immune inflammation. Networks of transcription factor (TF)–gene, miRNA–gene, and gene–disease interactions from the datasets were also constructed, and key gene regulators influencing the progression of these three diseases were further identified among the DEGs. Moreover, new drug targets were predicted based on these common DEGs, and molecular docking and molecular dynamics (MD) simulations were performed. Finally, a diagnostic model of COVID-19 was established based on these common DEGs. Taken together, the molecular and signaling pathways identified in this study may be related to the mechanisms by which SARS-CoV-2 infection affects renal function. These findings are significant for the effective treatment of COVID-19 in patients with kidney diseases

Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization

BackgroundSepsis-associated acute kidney injury (S-AKI) is considered to be associated with high morbidity and mortality, a commonly accepted model to predict mortality is urged consequently. This study used a machine learning model to identify vital variables associated with mortality in S-AKI patients in the hospital and predict the risk of death in the hospital. We hope that this model can help identify high-risk patients early and reasonably allocate medical resources in the intensive care unit (ICU).MethodsA total of 16,154 S-AKI patients from the Medical Information Mart for Intensive Care IV database were examined as the training set (80%) and the validation set (20%). Variables (129 in total) were collected, including basic patient information, diagnosis, clinical data, and medication records. We developed and validated machine learning models using 11 different algorithms and selected the one that performed the best. Afterward, recursive feature elimination was used to select key variables. Different indicators were used to compare the prediction performance of each model. The SHapley Additive exPlanations package was applied to interpret the best machine learning model in a web tool for clinicians to use. Finally, we collected clinical data of S-AKI patients from two hospitals for external validation.ResultsIn this study, 15 critical variables were finally selected, namely, urine output, maximum blood urea nitrogen, rate of injection of norepinephrine, maximum anion gap, maximum creatinine, maximum red blood cell volume distribution width, minimum international normalized ratio, maximum heart rate, maximum temperature, maximum respiratory rate, minimum fraction of inspired O2, minimum creatinine, minimum Glasgow Coma Scale, and diagnosis of diabetes and stroke. The categorical boosting algorithm model presented significantly better predictive performance [receiver operating characteristic (ROC): 0.83] than other models [accuracy (ACC): 75%, Youden index: 50%, sensitivity: 75%, specificity: 75%, F1 score: 0.56, positive predictive value (PPV): 44%, and negative predictive value (NPV): 92%]. External validation data from two hospitals in China were also well validated (ROC: 0.75).ConclusionsAfter selecting 15 crucial variables, a machine learning-based model for predicting the mortality of S-AKI patients was successfully established and the CatBoost model demonstrated best predictive performance

Thymosin beta 10 Prompted the VEGF-C Expression in Lung Cancer Cell

Background and objective Our previous study found that thymosin β10 overexpressed in lung cancer and positively correlated with differentiation, lymph node metastasis and stage of lung cancer. In this reasearch we aim to study the effects and mechanism of exogenous human recombinant Tβ10 on the expression of VEGF-C on non-small cell lung cancer. Methods After SPC, A549 and LK2 cells were treated with 100 ng/mL recombinant human Tβ10, the mRNA level of VEGF-C were detected by RT-PCR. The mean while the protein expression of VEGF-C, P-AKT and AKT were determined by Western blot assay. Results Exogenous recombinant human Tβ10 were significantly promote the expression levels of VEGF-C mRNA and protein while promoting the phosphorylation of AKT. Exogenous Tβ10 can promote the expression of VEGF-C mRNA and protein in lung cancer cell lines A549 and LK2 (P<0.05), and this effect can be inhibited by use AKT inhibitor LY294002 (P<0.05). Conclusion Tβ10 human recombinant proteins can promote the expression of VEGF-C by activating AKT phosphorylation in lung cancer cell lines

A study on the relationship between irregularity and hairiness of spun yarns

In this study, Photoshop software was used to do image analysis on the photos of spun yarns. The result showed that yarn could be divided into two parts: the surface hairs and the stem. Based on this finding, a mathematical model of yarn unevenness was built to analyze the relationship between yarn unevenness and surface hairiness. The relationships among the coefficients of mass variance of the yarn, the stem and the surface hairs, expressed as CVt, CVs and CVh, respectively, were investigated in detail. Results indicate that the CVs of an uneven yarn always coincides with the irregularity of the yarn hairiness. More specifically, the CVt of a yarn cannot be better than those of both yarn hairiness and stem (CVh and CVs), even if one of them is excessive. It is rare for CVt to be higher than CVs after removal of yarn hairs. In particular, it is irrational for the CVt value to be higher than both CVs and CVh, which prompts a rethinking of the exact distribution of yarn hairs on the yarn body

Longitudinal structures of zonal wind in the thermosphere by the ICON/MIGHTI and the main wave sources

Abstract In this study, the neutral wind observations from the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument onboard Ionospheric CONnections (ICON) are used to investigate the longitudinal structure of zonal wind between 100 and 300 km during daytime. The four-peaked structure in the longitudinal distribution between June and August is visually clear in the whole altitudinal range. The longitudinal wavenumber 1–4 patterns (WN1–WN4) are extracted, and the altitude–month distributions of WN1–WN4 and their contributions to the longitudinal structure are compared. The amplitudes of WN3 and WN4 show seasonal dependence, and the amplitude of WN4 exhibits obvious vertical propagation from the mesosphere and lower thermosphere (MLT) to the upper thermosphere in summer and autumn. WN1 is an important contributor to the longitudinal structure, WN4 is the primary contributor in the lower altitude ranges in summer and autumn at three latitudes. The contributions of WN3 (WN1) increase holistically with latitude in summer (spring, autumn, and winter). And the main wave sources of WN1–WN4 are further investigated in the 100–106 km and 210–300 km altitude regions. The main wave sources of WN1 and WN2 have complex variations with altitude, latitude, and season, while WN3 (WN4) is clearly influenced by DE2 (DE3 and SE2). Graphical Abstrac